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Artificial Intelligence (AI) has actually been around for decades. But only recently has it become an accessible tool for day-to-day tasks on our smartphones, picking strawberries, predicting crimes, and even English Language Teaching!

What is Artificial Intelligence?

A good working definition, which
applies to the general understanding of AI, is Artificial Intelligence involves machines or computers that work and
react like humans do.

The AI that is prevalent in
current technology is what we’d call Narrow
AI. That is to say it has a narrow focus and is very good at one or two
jobs. For example, Shazam is very good at
letting you know what song is playing, by listening to a snippet of the music,
but it can’t tell you how many tickets are left for the theatre tomorrow night,
or how tall Charles de Gaulle was.

An easy mistake to make is to
imagine AI as machines that can think like humans do. This is called General AI, where a program could
theoretically turn its hand to a variety of problems and, after a bit of
observation, take up the task itself, as a person might be able to.

This kind of multifaceted
intelligence isn’t replicable in computer programs (yet.) As Dr. Hadar Shemtov,
Director of Research at Google, said in response to a question from the
audience at an OUP dictionaries summit, “Computers
are actually a lot dumber than the average guy thinks… they still need to be
told what to do in the vast majority of cases.”

How does it work?

There are two basic ways AI can
work. The first is rules based – the
program is given a set of rules and it keeps applying these to the problem to
find an answer. The second is learning
based – the program observes, finds patterns and matches patterns
independently.

The difference between these two
is that one is taught, whilst one is learned.

This is why AI is mentioned with such frequency in recent years. Previously, AI was all rules based – meaning its capabilities were restricted by the rules that could be defined by programmers. Modern AI has shifted to learning based, making it exponentially more powerful and opening up many more exciting implications. This has become possible because the vast data sets, and the computing power to analyse them (required to help a program learn) are now available with modern technology.

So what is Machine Learning?

Machine Learning is when AI programs learn how to complete a task. Machine Learning involves a computer analysing large quantities of data, recognising patterns in the data, and drawing out conclusions or solutions from these patterns. Often, in order for patterns to become apparent, huge quantities of data need to be looked at. The more data available, the more likely the AI is going to produce an accurate answer.

The initial algorithm for how to
use the data is written by a human programmer, but the computer then applies
this to vast data sets. This means that AI can notice patterns and provide
answers far faster than any human – and sometimes provide answers humans would
have been incapable of ever producing. But, it also means that the quality of
the data needs to be good. If you input a poor data set into AI, you’re only
going to get poor output. If you want to see Machine Learning in action, Teachable Machine is a
great free tool developed by Google.

What
can we use AI for?

Well, just about anything. Uses
of AI have already done great things to make our modern and connected lives more
efficient and personalised. But there are also numerous potential benefits for
education, which could improve the working lives of teachers and the learning
journeys of students.

To date, Oxford University Press has already built products that make use of AI to personalise learning materials, we’ve partnered with Edwin to create an English tutor chatbot, and with Mobilinga to create interactive adventure stories, delivered via Alexa. We’re excited to continue exploring how we can make use of AI in education with our partners, using it to create new learning materials and content to help the world learn English.

Think you could partner with us? The Oxford University Press ELT Product and Innovation team are heading to the 2019 BETT conference in London later this month. Are you going? If you want to discuss potential partnerships with the team, please click the button below to get in touch and book a meeting.

Harry Cunningham is a Partnerships and Innovation Manager at Oxford
University Press in the ELT division. He’s focused on enhancing and bringing
OUP’s English Language Teaching content to life with the latest and best
technological solutions.

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